Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "173"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 173 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 55 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 53 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 173, Node N16:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459870 not_connected 100.00% 100.00% 100.00% 0.00% - - 26.744005 26.949836 17.231332 18.813168 10.548902 17.874166 7.388486 16.775615 0.0348 0.0393 0.0048 nan nan
2459869 not_connected 100.00% 100.00% 100.00% 0.00% - - 22.391893 21.584573 17.638787 18.914244 15.713573 22.951032 7.801794 11.537321 0.0402 0.0444 0.0056 nan nan
2459868 not_connected 100.00% 100.00% 100.00% 0.00% - - 24.316535 24.868718 25.209515 27.266349 10.716171 17.049818 8.729845 14.818265 0.0361 0.0405 0.0047 nan nan
2459867 not_connected 100.00% 100.00% 100.00% 0.00% - - 16.929706 17.846397 19.432359 21.498552 5.724581 9.897911 5.805763 10.203554 0.0357 0.0403 0.0049 nan nan
2459866 not_connected 100.00% 100.00% 100.00% 0.00% - - 19.561121 20.280696 18.781684 20.918137 6.167122 10.931914 2.426180 4.786145 0.0375 0.0436 0.0063 nan nan
2459865 not_connected 100.00% 100.00% 100.00% 0.00% - - 21.432748 22.883609 20.517455 23.416186 15.499775 23.912639 16.796374 15.484782 0.0344 0.0376 0.0037 nan nan
2459864 not_connected 100.00% 100.00% 100.00% 0.00% - - 26.431363 27.723283 6.235400 7.965877 8.119574 13.352090 8.913462 18.566983 0.0347 0.0388 0.0044 nan nan
2459863 not_connected 100.00% 100.00% 100.00% 0.00% - - 16.138584 16.841743 2.021015 2.742697 2.932723 5.070404 4.568594 8.156463 0.0350 0.0393 0.0046 nan nan
2459862 not_connected 100.00% 100.00% 100.00% 0.00% - - 16.054668 17.026201 6.627668 8.768463 12.579491 19.013582 3.212420 6.623062 0.0376 0.0420 0.0048 nan nan
2459861 not_connected 100.00% 100.00% 100.00% 0.00% - - 12.367704 12.661453 2.300276 3.177518 2.495087 3.205847 3.687945 8.261004 0.0352 0.0385 0.0039 nan nan
2459860 not_connected 100.00% 100.00% 100.00% 0.00% - - 13.447815 13.951901 6.733614 8.378125 14.511439 21.609203 3.404458 8.250327 0.0352 0.0391 0.0045 nan nan
2459859 not_connected 100.00% 100.00% 100.00% 0.00% - - 11.355791 11.869378 2.751442 3.632650 2.129901 2.757059 1.902082 5.028781 0.0351 0.0407 0.0058 nan nan
2459858 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 12.262893 12.642557 2.743509 3.566731 2.185882 2.860662 3.824983 8.684479 0.0356 0.0399 0.0048 1.215755 1.216269
2459857 not_connected 100.00% 100.00% 100.00% 0.00% - - 4.741087 5.646322 1.302030 1.201964 3.148143 3.947386 10.590021 28.037264 0.0359 0.0385 0.0037 nan nan
2459856 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 18.181028 19.080273 6.728889 8.144201 6.423664 12.026065 4.440006 11.483479 0.0376 0.0405 0.0035 1.235788 1.238320
2459855 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 18.955849 18.769545 6.018296 7.278260 2.880775 4.277992 2.176559 5.661800 0.0362 0.0414 0.0053 1.169616 1.170123
2459854 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 19.211766 17.125114 4.239003 5.124291 3.956433 4.243120 4.412265 10.967887 0.0362 0.0416 0.0057 1.242503 1.243754
2459853 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 15.764870 16.625512 6.637464 8.394032 6.789884 10.844642 5.479900 12.512843 0.0366 0.0425 0.0062 1.226591 1.228333
2459852 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 15.289200 16.388646 7.232548 9.505554 15.391762 19.806916 16.992208 16.714445 0.0390 0.0405 0.0031 1.204221 1.201693
2459851 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% nan nan inf inf nan nan nan nan nan nan nan 0.000000 0.000000
2459850 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 15.170927 19.604565 5.786790 7.792140 10.234207 19.737596 9.022780 25.056631 0.0380 0.0422 0.0051 1.178912 1.181671
2459849 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 17.557801 18.186316 13.198110 16.171441 7.067503 12.842642 5.778588 16.741868 0.0392 0.0427 0.0046 1.206110 1.205220
2459848 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% nan nan inf inf nan nan nan nan nan nan nan 0.000000 0.000000
2459847 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 18.374702 18.834115 5.778500 8.413164 22.048162 28.392086 2.605414 6.346705 0.0371 0.0389 0.0029 1.275058 1.282987

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 173: 2459870

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
173 N16 not_connected nn Shape 26.949836 26.744005 26.949836 17.231332 18.813168 10.548902 17.874166 7.388486 16.775615

Antenna 173: 2459869

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
173 N16 not_connected nn Temporal Variability 22.951032 22.391893 21.584573 17.638787 18.914244 15.713573 22.951032 7.801794 11.537321

Antenna 173: 2459868

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
173 N16 not_connected nn Power 27.266349 24.316535 24.868718 25.209515 27.266349 10.716171 17.049818 8.729845 14.818265

Antenna 173: 2459867

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
173 N16 not_connected nn Power 21.498552 16.929706 17.846397 19.432359 21.498552 5.724581 9.897911 5.805763 10.203554

Antenna 173: 2459866

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
173 N16 not_connected nn Power 20.918137 20.280696 19.561121 20.918137 18.781684 10.931914 6.167122 4.786145 2.426180

Antenna 173: 2459865

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
173 N16 not_connected nn Temporal Variability 23.912639 21.432748 22.883609 20.517455 23.416186 15.499775 23.912639 16.796374 15.484782

Antenna 173: 2459864

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
173 N16 not_connected nn Shape 27.723283 27.723283 26.431363 7.965877 6.235400 13.352090 8.119574 18.566983 8.913462

Antenna 173: 2459863

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
173 N16 not_connected nn Shape 16.841743 16.138584 16.841743 2.021015 2.742697 2.932723 5.070404 4.568594 8.156463

Antenna 173: 2459862

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
173 N16 not_connected nn Temporal Variability 19.013582 16.054668 17.026201 6.627668 8.768463 12.579491 19.013582 3.212420 6.623062

Antenna 173: 2459861

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
173 N16 not_connected nn Shape 12.661453 12.661453 12.367704 3.177518 2.300276 3.205847 2.495087 8.261004 3.687945

Antenna 173: 2459860

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
173 N16 not_connected nn Temporal Variability 21.609203 13.447815 13.951901 6.733614 8.378125 14.511439 21.609203 3.404458 8.250327

Antenna 173: 2459859

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
173 N16 not_connected nn Shape 11.869378 11.355791 11.869378 2.751442 3.632650 2.129901 2.757059 1.902082 5.028781

Antenna 173: 2459858

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
173 N16 not_connected nn Shape 12.642557 12.642557 12.262893 3.566731 2.743509 2.860662 2.185882 8.684479 3.824983

Antenna 173: 2459857

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
173 N16 not_connected nn Temporal Discontinuties 28.037264 5.646322 4.741087 1.201964 1.302030 3.947386 3.148143 28.037264 10.590021

Antenna 173: 2459856

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
173 N16 not_connected nn Shape 19.080273 18.181028 19.080273 6.728889 8.144201 6.423664 12.026065 4.440006 11.483479

Antenna 173: 2459855

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
173 N16 not_connected ee Shape 18.955849 18.769545 18.955849 7.278260 6.018296 4.277992 2.880775 5.661800 2.176559

Antenna 173: 2459854

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
173 N16 not_connected ee Shape 19.211766 17.125114 19.211766 5.124291 4.239003 4.243120 3.956433 10.967887 4.412265

Antenna 173: 2459853

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
173 N16 not_connected nn Shape 16.625512 16.625512 15.764870 8.394032 6.637464 10.844642 6.789884 12.512843 5.479900

Antenna 173: 2459852

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
173 N16 not_connected nn Temporal Variability 19.806916 15.289200 16.388646 7.232548 9.505554 15.391762 19.806916 16.992208 16.714445

Antenna 173: 2459851

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
173 N16 not_connected ee Shape nan nan nan inf inf nan nan nan nan

Antenna 173: 2459850

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
173 N16 not_connected nn Temporal Discontinuties 25.056631 15.170927 19.604565 5.786790 7.792140 10.234207 19.737596 9.022780 25.056631

Antenna 173: 2459849

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
173 N16 not_connected nn Shape 18.186316 17.557801 18.186316 13.198110 16.171441 7.067503 12.842642 5.778588 16.741868

Antenna 173: 2459848

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
173 N16 not_connected nn Shape nan nan nan inf inf nan nan nan nan

Antenna 173: 2459847

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
173 N16 not_connected nn Temporal Variability 28.392086 18.834115 18.374702 8.413164 5.778500 28.392086 22.048162 6.346705 2.605414
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